Abstract
Background ChIP-on-chip technology provides a genome-scale view of transcription factor (TF)/target interactions and a systemslevel window into transcriptional regulatory networks. However, while many studies have used ChIP-on-chip data to effectively discover new TF targets, statistical methods have fallen short of developing an accurate model to disassociate signals caused by experimental noise from those caused by true biological variation, thus leveraging the technology to provide high confidence predictions of the full range of interactions.
Highlights
ChIP-on-chip technology provides a genome-scale view of transcription factor (TF)/target interactions and a systemslevel window into transcriptional regulatory networks
statistical methods have fallen short of developing an accurate model to disassociate signals caused by experimental noise
from those caused by true biological variation
Summary
ChIP-on-chip significance analysis reveals ubiquitous transcription factor binding. Adam A Margolin*1,2,3, Teresa Palomero[2], Adolfo A Ferrando[2], Andrea Califano[1,2] and Gustavo Stolovitzky[3].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
